Josbel Garcia

P Dunedin Blue Jays

Age 23 RHP 6'0" / 165 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	MIX2 levels	15	5	37	4.58	3.93	18.0%	15.6%	—	K 11.8% · BB 19.2% · FIP 5.08
2025	21	MIX2 levels	20	0	31	6.75	4.18	16.4%	6.4%	—	K 13.2% · BB 7.7% · FIP 5.52
2026	22	MIX2 levels	27	0	52	4.70	4.01	21.9%	8.0%	—	K 15.9% · BB 10.6% · FIP 5.60
2027PROJ	23	MLBTOR	—	—	0	5.03	5.03	18.2%	10.7%	—
2028PROJ43% MLB	24	MLBTOR	15	0	16	4.86	4.79	19.7%	9.9%	-0.0
2029PROJ66% MLB	25	MLBTOR	21	0	22	4.72	4.65	20.5%	9.5%	-0.0

Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsJayson McKinley (age 23) · Matt Pidich (age 23) · Luis Eusebio (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 112

ERA5.03

FIP5.03

K%18.2%

BB%10.7%

K-BB%7.5%

Proj IP22

Value2027 · WAR

Runs saved vs league avg · 22 IP

Grades · Contract

Scouting Grades

K†4550

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to the standard WAR scale.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2022	18	ROK MLE	DSL Phillies Red	11	0	23	100	15	9	2	0%	2.1	10.2%	11.2%	-1.0%	2.4%	4.70	4.96	—
2022	18	ROK RAW	DSL Phillies Red	11	0	23	100	15	9	2	0%	2.1	15.0%	9.0%	6.0%	2.0%	4.70	4.10	—
2023	19	ROK MLE	DSL Phillies White	14	1	32	133	15	6	1	7%	2.3	7.7%	5.6%	2.0%	1.3%	1.69	3.89	—
2023	19	ROK RAW	DSL Phillies White	14	1	32	133	15	6	1	7%	2.3	11.3%	4.5%	6.8%	0.8%	1.69	3.13	—
2024	20	MIX MLE	2 levels	15	5	37	167	30	26	1	33%	2.5	11.8%	19.2%	-7.5%	1.0%	4.58	5.08	—
2024	20	MIX MLE	2 levels	15	5	37	167	30	26	1	33%	2.5	11.8%	19.2%	-7.5%	1.0%	4.58	5.08	—
2024	20	MIX RAW	2 levels	15	5	37	167	30	26	1	33%	2.5	18.0%	15.6%	2.4%	0.6%	4.58	3.93	—
2025	21	MIX MLE	2 levels	20	0	31	140	23	9	4	0%	1.5	13.2%	7.7%	5.5%	4.7%	6.75	5.52	—
2025	21	MIX MLE	2 levels	20	0	31	140	23	9	4	0%	1.5	13.2%	7.7%	5.5%	4.7%	6.75	5.52	—
2025	21	MIX RAW	2 levels	20	0	31	140	23	9	4	0%	1.5	16.4%	6.4%	10.0%	2.9%	6.75	4.18	—
2026	22	MIX MLE	2 levels	27	0	52	224	49	18	7	0%	1.9	15.9%	10.6%	5.3%	4.6%	4.70	5.60	—
2026	22	MIX MLE	2 levels	27	0	52	224	49	18	7	0%	1.9	15.9%	10.6%	5.3%	4.6%	4.70	5.60	—
2026	22	MIX RAW	2 levels	27	0	52	224	49	18	7	0%	1.9	21.9%	8.0%	13.8%	3.1%	4.70	4.01	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	TOR	—	—	0	—	—	—	—	—	—	18.2%	10.7%	7.5%	3.2%	5.03	5.03	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	TOR	35	0	36	153	30	15	5	0%	1.0	19.7%	9.9%	9.7%	3.1%	4.86	4.79	-0.1
2029	25	MLB MLE	TOR	31	0	33	138	28	13	4	0%	1.1	20.5%	9.5%	11.0%	3.1%	4.72	4.65	-0.0
2028	24	MLB CTX	TOR	15	0	16	68	13	7	2	0%	1.1	19.7%	9.9%	9.7%	3.1%	4.86	4.79	-0.0
2029	25	MLB CTX	TOR	21	0	22	93	19	9	3	0%	1.0	20.5%	9.5%	11.0%	3.1%	4.72	4.65	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		35	0	37	157	32	15	5	0%	1.1	20.1%	9.7%	10.5%	3.1%	4.78	4.33	+0.1
/ 200 IP	—	RAW		190	0	200	844	172	81	27	0%	1.1	20.1%	9.7%	10.5%	3.1%	4.78	4.33	+0.5
Career	—	MLE		87	6	175	764	94	85	22	7%	2.0	12.3%	11.2%	1.1%	2.9%	4.48	5.09	-0.1
/ 200 IP	—	MLE		100	7	200	875	108	98	26	7%	2.0	12.3%	11.2%	1.1%	2.9%	4.48	5.09	-0.4

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 ADunedin Blue Jays · 44 IPFIP 4.35 → 5.60 (+1.25)K% 21.5% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.50%	—	×0.740	15.91%
BB% (unintentional) /BF	9.00%	—	×1.180	10.62%
HR / BF /BF	3.50%	÷1.000	×1.300	4.55%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 4.35 → 5.60, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2026 ROKFCL Blue Jays · 7 IPFIP 0.99 → 1.66 (+0.68)K% 25.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.680	17.00%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 0.99 → 1.66, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 ROKFCL Phillies · 22 IPFIP 3.92 → 5.52 (+1.60)K% 19.4% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.39%	—	×0.680	13.18%
BB% (unintentional) /BF	6.12%	—	×1.250	7.65%
HR / BF /BF	3.06%	÷0.917	×1.400	4.68%

Result: FIP 3.92 → 5.52, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 AClearwater Threshers · 8 IPFIP 4.51 → 5.14 (+0.63)K% 9.5% → 7.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	9.52%	—	×0.740	7.05%
BB% (unintentional) /BF	7.14%	—	×1.180	8.43%
HR / BF /BF	2.38%	÷1.083	×1.300	2.86%

Result: FIP 4.51 → 5.14, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 ROKFCL Phillies · 35 IPFIP 3.94 → 5.08 (+1.14)K% 17.3% → 11.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.31%	—	×0.680	11.77%
BB% (unintentional) /BF	15.38%	—	×1.250	19.23%
HR / BF /BF	0.64%	÷0.924	×1.400	0.97%

Result: FIP 3.94 → 5.08, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2023 ROKDSL Phillies White · 32 IPFIP 3.13 → 3.89 (+0.76)K% 11.3% → 7.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.28%	—	×0.680	7.67%
BB% (unintentional) /BF	4.51%	—	×1.250	5.64%
HR / BF /BF	0.75%	÷0.794	×1.400	1.33%

Result: FIP 3.13 → 3.89, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2022 ROKDSL Phillies Red · 23 IPFIP 4.07 → 4.96 (+0.89)K% 15.0% → 10.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.00%	—	×0.680	10.20%
BB% (unintentional) /BF	9.00%	—	×1.250	11.25%
HR / BF /BF	2.00%	÷1.187	×1.400	2.36%

Result: FIP 4.07 → 4.96, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Josbel Garcia (OGILVIE)	—	—	5.03	18.2%	10.7%	3.2%	—	4.72	20.1%	10.3%	69	-0.31	—	—	—
Jayson McKinley R 2017 · 4.39 FIP	23	SU	4.39	17.5%	11.4%	2.4%	.308	3.60	20.4%	11.3%	134	-0.79	2.35	173	91
Matt Pidich R 2018 · 4.42 FIP	23	SU	4.42	17.1%	8.3%	3.1%	.303	4.08	20.8%	13.3%	115	-0.34	4.05	196	89
Luis Eusebio R 2019 · 4.92 FIP	23	SU	4.92	18.2%	10.6%	3.7%	.295	—	—	—	—	—	4.79	131	89
Todd Peterson R 2021 · 5.11 FIP	23	SW	5.11	18.4%	10.3%	4.1%	.279	4.83	15.0%	4.3%	124	-0.28	4.45	175	88
Sean Isaac R 2016 · 4.27 FIP	23	SU	4.27	19.5%	12.3%	2.3%	.342	3.76	25.0%	10.7%	128	-0.51	3.27	155	88
Heath Holder R 2016 · 4.16 FIP	23	SU	4.16	21.1%	10.1%	2.8%	.287	3.30	22.3%	13.1%	247	-0.86	2.94	367	87
Anyelo Leclerc R 2015 · 5.00 FIP	23	SU	5.00	16.2%	9.8%	3.7%	.326	4.65	15.9%	6.1%	96	-0.35	4.65	140	87
Colby Morris R 2021 · 4.11 FIP	24	SU	4.11	20.4%	10.7%	2.5%	.291	5.76	16.2%	4.4%	54	+1.65	4.11	105	87
Thomas Balboni Jr. R 2023 · 3.99 FIP	23	SU	3.99	17.5%	10.9%	1.8%	.331	3.47	28.1%	14.3%	79	-0.52	2.99	122	87
Hayden Snelsire R 2024 · 5.10 FIP	23	SU	5.10	18.9%	13.8%	3.4%	.272	4.28	20.0%	13.7%	135	-0.82	3.83	178	86
Junior Rincon R 2015 · 4.93 FIP	23	SU	4.93	17.8%	13.8%	2.9%	.318	3.75	17.6%	5.1%	82	-1.18	3.52	113	86
Dylan Simmons R 2024 · 3.85 FIP	23	SU	3.85	17.8%	9.4%	1.9%	.295	5.10	12.7%	0.6%	74	+1.25	3.85	125	86
Miles Mikolas R 2012 · 4.56 FIP	23	SU	4.56	16.0%	10.4%	2.7%	.275	4.29	14.9%	8.6%	57	-0.27	3.13	1,386	86
Miguel Guerrero R 2023 · 4.56 FIP	23	SU	4.56	18.1%	10.3%	3.1%	.288	—	—	—	—	—	4.56	171	85
Carlos Lequerica R 2024 · 3.92 FIP	23	SU	3.92	16.3%	10.0%	1.7%	.302	5.06	16.9%	5.1%	96	+1.14	3.92	129	85
Julio Mateo R 2002 · 4.54 FIP	24	SU	4.54	16.0%	12.8%	2.1%	.277	4.23	17.5%	13.8%	232	-0.31	3.42	318	85
Stephen Perakslis R 2015 · 4.54 FIP	24	SU	4.54	14.6%	9.9%	2.6%	.254	3.99	16.9%	9.9%	190	-0.55	3.07	211	85
Reece Karalus R 2017 · 4.91 FIP	23	SU	4.91	14.0%	9.1%	3.4%	.303	4.73	15.4%	3.5%	55	-0.18	4.73	149	85
Francisco Del Rosario R 2006 · 5.13 FIP	25	SU	5.13	19.4%	13.0%	3.7%	.290	3.93	19.7%	10.3%	26	-1.20	3.93	194	84
Tyler Schoff R 2022 · 4.25 FIP	23	SU	4.25	19.6%	10.8%	2.6%	.350	3.72	23.8%	15.7%	93	-0.53	3.69	190	84

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	0.5	30	19.6%	9.9%	1.21	4.85
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Bill Pleis ('61-'66, -0 WAR*)	1.4	56	19.7%*	9.8%*	1.15*	4.53*